Automatic detection and prevention of injection attacks

ABSTRACT

In one embodiment, a controller in a network may receive an injected command to be executed by an application from an application monitoring agent operating in the network. The injected command may be intercepted by the application monitoring agent prior to execution of the injected command by the application. The controller may then use a security algorithm to determine whether the injected command is malicious. If it is determined that the injected command is not malicious, the controller may enable the application to execute the injected command. Conversely, if it is determined that the injected command is malicious, the controller may prevent the application from executing the injected command.

TECHNICAL FIELD

The present disclosure relates generally to computer systems, and, moreparticularly, to automatic detection and prevention of injectionattacks.

BACKGROUND

The Internet and the World Wide Web have enabled the proliferation ofweb services available for virtually all types of businesses. Due to theaccompanying complexity of the infrastructure supporting the webservices, it is becoming increasingly difficult to maintain the highestlevel of service performance and user experience to keep up with theincrease in web services. For example, it can be challenging to piecetogether monitoring and logging data across disparate systems, tools,and layers in a network architecture. Moreover, even when data can beobtained, it is difficult to directly connect the chain of events andcause and effect.

In addition, applications are built on different frameworks andlibraries which may inherently have security loopholes, making themvulnerable. Despite using framework security features and other securityapplications, customer applications are vulnerable to security riskslike injection flaws, sensitive data exposure, and so on.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments herein may be better understood by referring to thefollowing description in conjunction with the accompanying drawings inwhich like reference numerals indicate identically or functionallysimilar elements, of which:

FIGS. 1A-1B illustrate an example computer network;

FIG. 2 illustrates an example computing device/node;

FIG. 3 illustrates an example application intelligence platform;

FIG. 4 illustrates an example system for implementing the exampleapplication intelligence platform;

FIG. 5 illustrates an example computing system implementing thedisclosed technology;

FIG. 6 illustrates an example simplified architecture for automaticdetection and prevention of injection attacks in accordance with one ormore embodiments described herein;

FIGS. 7A-7B illustrate an example of SQL injection prevention inaccordance with one or more embodiments described herein;

FIGS. 8A-8B illustrate an example of command injection prevention inaccordance with one or more embodiments described herein; and

FIG. 9 illustrates an example simplified procedure for automaticdetection and prevention of injection attacks in accordance with one ormore embodiments described herein.

DESCRIPTION OF EXAMPLE EMBODIMENTS Overview

According to one or more embodiments of the disclosure, a controller ina network may receive an injected command to be executed by anapplication from an application monitoring agent operating in thenetwork. The injected command may be intercepted by the applicationmonitoring agent prior to execution of the injected command by theapplication. The controller may then use a security algorithm todetermine whether the injected command is malicious. If it is determinedthat the injected command is not malicious, the controller may enablethe application to execute the injected command. Conversely, if it isdetermined that the injected command is malicious, the controller mayprevent the application from executing the injected command.

Other embodiments are described below, and this overview is not meant tolimit the scope of the present disclosure.

Description

A computer network is a geographically distributed collection of nodesinterconnected by communication links and segments for transporting databetween end nodes, such as personal computers and workstations, or otherdevices, such as sensors, etc. Many types of networks are available,ranging from local area networks (LANs) to wide area networks (WANs).LANs typically connect the nodes over dedicated private communicationslinks located in the same general physical location, such as a buildingor campus. WANs, on the other hand, typically connect geographicallydispersed nodes over long-distance communications links, such as commoncarrier telephone lines, optical lightpaths, synchronous opticalnetworks (SONET), synchronous digital hierarchy (SDH) links, orPowerline Communications (PLC), and others. The Internet is an exampleof a WAN that connects disparate networks throughout the world,providing global communication between nodes on various networks. Othertypes of networks, such as field area networks (FANs), neighborhood areanetworks (NANs), personal area networks (PANs), enterprise networks,etc. may also make up the components of any given computer network.

The nodes typically communicate over the network by exchanging discreteframes or packets of data according to predefined protocols, such as theTransmission Control Protocol/Internet Protocol (TCP/IP). In thiscontext, a protocol consists of a set of rules defining how the nodesinteract with each other. Computer networks may be furtherinterconnected by an intermediate network node, such as a router, toextend the effective “size” of each network.

Smart object networks, such as sensor networks, in particular, are aspecific type of network having spatially distributed autonomous devicessuch as sensors, actuators, etc., that cooperatively monitor physical orenvironmental conditions at different locations, such as, e.g.,energy/power consumption, resource consumption (e.g., water/gas/etc. foradvanced metering infrastructure or “AMI” applications) temperature,pressure, vibration, sound, radiation, motion, pollutants, etc. Othertypes of smart objects include actuators, e.g., responsible for turningon/off an engine or perform any other actions. Sensor networks, a typeof smart object network, are typically shared-media networks, such aswireless or power-line communication networks. That is, in addition toone or more sensors, each sensor device (node) in a sensor network maygenerally be equipped with a radio transceiver or other communicationport, a microcontroller, and an energy source, such as a battery.Generally, size and cost constraints on smart object nodes (e.g.,sensors) result in corresponding constraints on resources such asenergy, memory, computational speed and bandwidth.

FIG. 1A is a schematic block diagram of an example computer network 100illustratively comprising nodes/devices, such as a plurality ofrouters/devices interconnected by links or networks, as shown. Forexample, customer edge (CE) routers 110 may be interconnected withprovider edge (PE) routers 120 (e.g., PE-1, PE-2, and PE-3) in order tocommunicate across a core network, such as an illustrative networkbackbone 130. For example, routers 110, 120 may be interconnected by thepublic Internet, a multiprotocol label switching (MPLS) virtual privatenetwork (VPN), or the like. Data packets 140 (e.g., traffic/messages)may be exchanged among the nodes/devices of the computer network 100over links using predefined network communication protocols such as theTransmission Control Protocol/Internet Protocol (TCP/IP), User DatagramProtocol (UDP), Asynchronous Transfer Mode (ATM) protocol, Frame Relayprotocol, or any other suitable protocol. Those skilled in the art willunderstand that any number of nodes, devices, links, etc. may be used inthe computer network, and that the view shown herein is for simplicity.

In some implementations, a router or a set of routers may be connectedto a private network (e.g., dedicated leased lines, an optical network,etc.) or a virtual private network (VPN), such as an MPLS VPN thanks toa carrier network, via one or more links exhibiting very differentnetwork and service level agreement characteristics.

FIG. 1B illustrates an example of network 100 in greater detail,according to various embodiments. As shown, network backbone 130 mayprovide connectivity between devices located in different geographicalareas and/or different types of local networks. For example, network 100may comprise local/branch networks 160, 162 that include devices/nodes10-16 and devices/nodes 18-20, respectively, as well as a datacenter/cloud environment 150 that includes servers 152-154. Notably,local networks 160-162 and data center/cloud environment 150 may belocated in different geographic locations. Servers 152-154 may include,in various embodiments, any number of suitable servers or othercloud-based resources. As would be appreciated, network 100 may includeany number of local networks, data centers, cloud environments,devices/nodes, servers, etc.

In some embodiments, the techniques herein may be applied to othernetwork topologies and configurations. For example, the techniquesherein may be applied to peering points with high-speed links, datacenters, etc. Furthermore, in various embodiments, network 100 mayinclude one or more mesh networks, such as an Internet of Thingsnetwork. Loosely, the term “Internet of Things” or “IoT” refers touniquely identifiable objects (things) and their virtual representationsin a network-based architecture. In particular, the next frontier in theevolution of the Internet is the ability to connect more than justcomputers and communications devices, but rather the ability to connect“objects” in general, such as lights, appliances, vehicles, heating,ventilating, and air-conditioning (HVAC), windows and window shades andblinds, doors, locks, etc. The “Internet of Things” thus generallyrefers to the interconnection of objects (e.g., smart objects), such assensors and actuators, over a computer network (e.g., via IP), which maybe the public Internet or a private network.

Notably, shared-media mesh networks, such as wireless networks, areoften on what is referred to as Low-Power and Lossy Networks (LLNs),which are a class of network in which both the routers and theirinterconnect are constrained: LLN routers typically operate withconstraints, e.g., processing power, memory, and/or energy (battery),and their interconnects are characterized by, illustratively, high lossrates, low data rates, and/or instability. LLNs are comprised ofanything from a few dozen to thousands or even millions of LLN routers,and support point-to-point traffic (between devices inside the LLN),point-to-multipoint traffic (from a central control point such at theroot node to a subset of devices inside the LLN), andmultipoint-to-point traffic (from devices inside the LLN towards acentral control point). Often, an IoT network is implemented with anLLN-like architecture. For example, as shown, local network 160 may bean LLN in which CE-2 operates as a root node for nodes/devices 10-16 inthe local mesh, in some embodiments.

FIG. 2 is a schematic block diagram of an example computing device(e.g., apparatus) 200 that may be used with one or more embodimentsdescribed herein, e.g., as any of the devices shown in FIGS. 1A-1Babove, and particularly as specific devices as described further below.The device may comprise one or more network interfaces 210 (e.g., wired,wireless, etc.), at least one processor 220, and a memory 240interconnected by a system bus 250, as well as a power supply 260 (e.g.,battery, plug-in, etc.).

The network interface(s) 210 contain the mechanical, electrical, andsignaling circuitry for communicating data over links coupled to thenetwork 100, e.g., providing a data connection between device 200 andthe data network, such as the Internet. The network interfaces may beconfigured to transmit and/or receive data using a variety of differentcommunication protocols. For example, interfaces 210 may include wiredtransceivers, wireless transceivers, cellular transceivers, or the like,each to allow device 200 to communicate information to and from a remotecomputing device or server over an appropriate network. The same networkinterfaces 210 also allow communities of multiple devices 200 tointerconnect among themselves, either peer-to-peer, or up and down ahierarchy. Note, further, that the nodes may have two different types ofnetwork connections 210, e.g., wireless and wired/physical connections,and that the view herein is merely for illustration. Also, while thenetwork interface 210 is shown separately from power supply 260, fordevices using powerline communication (PLC) or Power over Ethernet(PoE), the network interface 210 may communicate through the powersupply 260, or may be an integral component of the power supply.

The memory 240 comprises a plurality of storage locations that areaddressable by the processor 220 and the network interfaces 210 forstoring software programs and data structures associated with theembodiments described herein. The processor 220 may comprise hardwareelements or hardware logic adapted to execute the software programs andmanipulate the data structures 245. An operating system 242, portions ofwhich are typically resident in memory 240 and executed by theprocessor, functionally organizes the device by, among other things,invoking operations in support of software processes and/or servicesexecuting on the device. These software processes and/or services maycomprise one or more functional processes 246, and on certain devices,an illustrative “injection attack mitigation” process 248, as describedherein. Notably, functional processes 246, when executed by processor(s)220, cause each particular device 200 to perform the various functionscorresponding to the particular device's purpose and generalconfiguration. For example, a router would be configured to operate as arouter, a server would be configured to operate as a server, an accesspoint (or gateway) would be configured to operate as an access point (orgateway), a client device would be configured to operate as a clientdevice, and so on.

It will be apparent to those skilled in the art that other processor andmemory types, including various computer-readable media, may be used tostore and execute program instructions pertaining to the techniquesdescribed herein. Also, while the description illustrates variousprocesses, it is expressly contemplated that various processes may beembodied as modules configured to operate in accordance with thetechniques herein (e.g., according to the functionality of a similarprocess). Further, while the processes have been shown separately, thoseskilled in the art will appreciate that processes may be routines ormodules within other processes.

Application Intelligence Platform

The embodiments herein relate to an application intelligence platformfor application performance management. In one aspect, as discussed withrespect to FIGS. 3-5 below, performance within a networking environmentmay be monitored, specifically by monitoring applications and entities(e.g., transactions, tiers, nodes, and machines) in the networkingenvironment using agents installed at individual machines at theentities. As an example, applications may be configured to run on one ormore machines (e.g., a customer will typically run one or more nodes ona machine, where an application consists of one or more tiers, and atier consists of one or more nodes). The agents collect data associatedwith the applications of interest and associated nodes and machineswhere the applications are being operated. Examples of the collecteddata may include performance data (e.g., metrics, metadata, etc.) andtopology data (e.g., indicating relationship information). Theagent-collected data may then be provided to one or more servers orcontrollers to analyze the data.

FIG. 3 is a block diagram of an example application intelligenceplatform 300 that can implement one or more aspects of the techniquesherein. The application intelligence platform is a system that monitorsand collects metrics of performance data for an application environmentbeing monitored. At the simplest structure, the application intelligenceplatform includes one or more agents 310 and one or moreservers/controllers 320. Note that while FIG. 3 shows four agents (e.g.,Agent 1 through Agent 4) communicatively linked to a single controller,the total number of agents and controllers can vary based on a number offactors including the number of applications monitored, how distributedthe application environment is, the level of monitoring desired, thelevel of user experience desired, and so on.

The controller 320 is the central processing and administration serverfor the application intelligence platform. The controller 320 serves abrowser-based user interface (UI) 330 that is the primary interface formonitoring, analyzing, and troubleshooting the monitored environment.The controller 320 can control and manage monitoring of businesstransactions (described below) distributed over application servers.Specifically, the controller 320 can receive runtime data from agents310 (and/or other coordinator devices), associate portions of businesstransaction data, communicate with agents to configure collection ofruntime data, and provide performance data and reporting through theinterface 330. The interface 330 may be viewed as a web-based interfaceviewable by a client device 340. In some implementations, a clientdevice 340 can directly communicate with controller 320 to view aninterface for monitoring data. The controller 320 can include avisualization system 350 for displaying the reports and dashboardsrelated to the disclosed technology. In some implementations, thevisualization system 350 can be implemented in a separate machine (e.g.,a server) different from the one hosting the controller 320.

Notably, in an illustrative Software as a Service (SaaS) implementation,a controller instance 320 may be hosted remotely by a provider of theapplication intelligence platform 300. In an illustrative on-premises(On-Prem) implementation, a controller instance 320 may be installedlocally and self-administered.

The controllers 320 receive data from different agents 310 (e.g., Agents1-4) deployed to monitor applications, databases and database servers,servers, and end user clients for the monitored environment. Any of theagents 310 can be implemented as different types of agents with specificmonitoring duties. For example, application agents may be installed oneach server that hosts applications to be monitored. Instrumenting anagent adds an application agent into the runtime process of theapplication.

Database agents, for example, may be software (e.g., a Java program)installed on a machine that has network access to the monitoreddatabases and the controller. Database agents query the monitoreddatabases in order to collect metrics and pass those metrics along fordisplay in a metric browser (e.g., for database monitoring and analysiswithin databases pages of the controller's UI 330). Multiple databaseagents can report to the same controller. Additional database agents canbe implemented as backup database agents to take over for the primarydatabase agents during a failure or planned machine downtime. Theadditional database agents can run on the same machine as the primaryagents or on different machines. A database agent can be deployed ineach distinct network of the monitored environment. Multiple databaseagents can run under different user accounts on the same machine.

Standalone machine agents, on the other hand, may be standalone programs(e.g., standalone Java programs) that collect hardware-relatedperformance statistics from the servers (or other suitable devices) inthe monitored environment. The standalone machine agents can be deployedon machines that host application servers, database servers, messagingservers, Web servers, etc. A standalone machine agent has an extensiblearchitecture (e.g., designed to accommodate changes).

End user monitoring (EUM) may be performed using browser agents andmobile agents to provide performance information from the point of viewof the client, such as a web browser or a mobile native application.Through EUM, web use, mobile use, or combinations thereof (e.g., by realusers or synthetic agents) can be monitored based on the monitoringneeds. Notably, browser agents (e.g., agents 310) can include Reportersthat report monitored data to the controller.

Monitoring through browser agents and mobile agents are generally unlikemonitoring through application agents, database agents, and standalonemachine agents that are on the server. In particular, browser agents maygenerally be embodied as small files using web-based technologies, suchas JavaScript agents injected into each instrumented web page (e.g., asclose to the top as possible) as the web page is served, and areconfigured to collect data. Once the web page has completed loading, thecollected data may be bundled into a beacon and sent to an EUMprocess/cloud for processing and made ready for retrieval by thecontroller. Browser real user monitoring (Browser RUM) provides insightsinto the performance of a web application from the point of view of areal or synthetic end user. For example, Browser RUM can determine howspecific Ajax or iframe calls are slowing down page load time and howserver performance impact end user experience in aggregate or inindividual cases.

A mobile agent, on the other hand, may be a small piece of highlyperformant code that gets added to the source of the mobile application.Mobile RUM provides information on the native mobile application (e.g.,iOS or Android applications) as the end users actually use the mobileapplication. Mobile RUM provides visibility into the functioning of themobile application itself and the mobile application's interaction withthe network used and any server-side applications with which the mobileapplication communicates.

Application Intelligence Monitoring: The disclosed technology canprovide application intelligence data by monitoring an applicationenvironment that includes various services such as web applicationsserved from an application server (e.g., Java virtual machine (JVM),Internet Information Services (IIS), Hypertext Preprocessor (PHP) Webserver, etc.), databases or other data stores, and remote services suchas message queues and caches. The services in the applicationenvironment can interact in various ways to provide a set of cohesiveuser interactions with the application, such as a set of user servicesapplicable to end user customers.

Application Intelligence Modeling: Entities in the applicationenvironment (such as the JBoss service, MQSeries modules, and databases)and the services provided by the entities (such as a login transaction,service or product search, or purchase transaction) may be mapped to anapplication intelligence model. In the application intelligence model, abusiness transaction represents a particular service provided by themonitored environment. For example, in an e-commerce application,particular real-world services can include a user logging in, searchingfor items, or adding items to the cart. In a content portal, particularreal-world services can include user requests for content such assports, business, or entertainment news. In a stock trading application,particular real-world services can include operations such as receivinga stock quote, buying, or selling stocks.

Business Transactions: A business transaction representation of theparticular service provided by the monitored environment provides a viewon performance data in the context of the various tiers that participatein processing a particular request. A business transaction, which mayeach be identified by a unique business transaction identification (ID),represents the end-to-end processing path used to fulfill a servicerequest in the monitored environment (e.g., adding items to a shoppingcart, storing information in a database, purchasing an item online,etc.). Thus, a business transaction is a type of user-initiated actionin the monitored environment defined by an entry point and a processingpath across application servers, databases, and potentially many otherinfrastructure components. Each instance of a business transaction is anexecution of that transaction in response to a particular user request(e.g., a socket call, illustratively associated with the TCP layer). Abusiness transaction can be created by detecting incoming requests at anentry point and tracking the activity associated with request at theoriginating tier and across distributed components in the applicationenvironment (e.g., associating the business transaction with a 4-tupleof a source IP address, source port, destination IP address, anddestination port). A flow map can be generated for a businesstransaction that shows the touch points for the business transaction inthe application environment. In one embodiment, a specific tag may beadded to packets by application specific agents for identifying businesstransactions (e.g., a custom header field attached to a hypertexttransfer protocol (HTTP) payload by an application agent, or by anetwork agent when an application makes a remote socket call), such thatpackets can be examined by network agents to identify the businesstransaction identifier (ID) (e.g., a Globally Unique Identifier (GUID)or Universally Unique Identifier (UUID)).

Performance monitoring can be oriented by business transaction to focuson the performance of the services in the application environment fromthe perspective of end users. Performance monitoring based on businesstransactions can provide information on whether a service is available(e.g., users can log in, check out, or view their data), response timesfor users, and the cause of problems when the problems occur.

A business application is the top-level container in the applicationintelligence model. A business application contains a set of relatedservices and business transactions. In some implementations, a singlebusiness application may be needed to model the environment. In someimplementations, the application intelligence model of the applicationenvironment can be divided into several business applications. Businessapplications can be organized differently based on the specifics of theapplication environment. One consideration is to organize the businessapplications in a way that reflects work teams in a particularorganization, since role-based access controls in the Controller UI areoriented by business application.

A node in the application intelligence model corresponds to a monitoredserver or JVM in the application environment. A node is the smallestunit of the modeled environment. In general, a node corresponds to anindividual application server, JVM, or Common Language Runtime (CLR) onwhich a monitoring Agent is installed. Each node identifies itself inthe application intelligence model. The Agent installed at the node isconfigured to specify the name of the node, tier, and businessapplication under which the Agent reports data to the Controller.

Business applications contain tiers, the unit in the applicationintelligence model that includes one or more nodes. Each node representsan instrumented service (such as a web application). While a node can bea distinct application in the application environment, in theapplication intelligence model, a node is a member of a tier, which,along with possibly many other tiers, make up the overall logicalbusiness application.

Tiers can be organized in the application intelligence model dependingon a mental model of the monitored application environment. For example,identical nodes can be grouped into a single tier (such as a cluster ofredundant servers). In some implementations, any set of nodes, identicalor not, can be grouped for the purpose of treating certain performancemetrics as a unit into a single tier.

The traffic in a business application flows among tiers and can bevisualized in a flow map using lines among tiers. In addition, the linesindicating the traffic flows among tiers can be annotated withperformance metrics. In the application intelligence model, there maynot be any interaction among nodes within a single tier. Also, in someimplementations, an application agent node cannot belong to more thanone tier. Similarly, a machine agent cannot belong to more than onetier. However, more than one machine agent can be installed on amachine.

A backend is a component that participates in the processing of abusiness transaction instance. A backend is not instrumented by anagent. A backend may be a web server, database, message queue, or othertype of service. The agent recognizes calls to these backend servicesfrom instrumented code (called exit calls). When a service is notinstrumented and cannot continue the transaction context of the call,the agent determines that the service is a backend component. The agentpicks up the transaction context at the response at the backend andcontinues to follow the context of the transaction from there.

Performance information is available for the backend call. For detailedtransaction analysis for the leg of a transaction processed by thebackend, the database, web service, or other application need to beinstrumented.

The application intelligence platform uses both self-learned baselinesand configurable thresholds to help identify application issues. Acomplex distributed application has a large number of performancemetrics and each metric is important in one or more contexts. In suchenvironments, it is difficult to determine the values or ranges that arenormal for a particular metric; set meaningful thresholds on which tobase and receive relevant alerts; and determine what is a “normal”metric when the application or infrastructure undergoes change. Forthese reasons, the disclosed application intelligence platform canperform anomaly detection based on dynamic baselines or thresholds.

The disclosed application intelligence platform automatically calculatesdynamic baselines for the monitored metrics, defining what is “normal”for each metric based on actual usage. The application intelligenceplatform uses these baselines to identify subsequent metrics whosevalues fall out of this normal range. Static thresholds that are tediousto set up and, in rapidly changing application environments,error-prone, are no longer needed.

The disclosed application intelligence platform can use configurablethresholds to maintain service level agreements (SLAs) and ensureoptimum performance levels for system by detecting slow, very slow, andstalled transactions. Configurable thresholds provide a flexible way toassociate the right business context with a slow request to isolate theroot cause.

In addition, health rules can be set up with conditions that use thedynamically generated baselines to trigger alerts or initiate othertypes of remedial actions when performance problems are occurring or maybe about to occur.

For example, dynamic baselines can be used to automatically establishwhat is considered normal behavior for a particular application.Policies and health rules can be used against baselines or other healthindicators for a particular application to detect and troubleshootproblems before users are affected. Health rules can be used to definemetric conditions to monitor, such as when the “average response time isfour times slower than the baseline”. The health rules can be createdand modified based on the monitored application environment.

Examples of health rules for testing business transaction performancecan include business transaction response time and business transactionerror rate. For example, health rule that tests whether the businesstransaction response time is much higher than normal can define acritical condition as the combination of an average response timegreater than the default baseline by 3 standard deviations and a loadgreater than 50 calls per minute. In some implementations, this healthrule can define a warning condition as the combination of an averageresponse time greater than the default baseline by 2 standard deviationsand a load greater than 100 calls per minute. In some implementations,the health rule that tests whether the business transaction error rateis much higher than normal can define a critical condition as thecombination of an error rate greater than the default baseline by 3standard deviations and an error rate greater than 10 errors per minuteand a load greater than 50 calls per minute. In some implementations,this health rule can define a warning condition as the combination of anerror rate greater than the default baseline by 2 standard deviationsand an error rate greater than 5 errors per minute and a load greaterthan 50 calls per minute. These are non-exhaustive and non-limitingexamples of health rules and other health rules can be defined asdesired by the user.

Policies can be configured to trigger actions when a health rule isviolated or when any event occurs. Triggered actions can includenotifications, diagnostic actions, auto-scaling capacity, runningremediation scripts.

Most of the metrics relate to the overall performance of the applicationor business transaction (e.g., load, average response time, error rate,etc.) or of the application server infrastructure (e.g., percentage CPUbusy, percentage of memory used, etc.). The Metric Browser in thecontroller UI can be used to view all of the metrics that the agentsreport to the controller.

In addition, special metrics called information points can be created toreport on how a given business (as opposed to a given application) isperforming. For example, the performance of the total revenue for acertain product or set of products can be monitored. Also, informationpoints can be used to report on how a given code is performing, forexample how many times a specific method is called and how long it istaking to execute. Moreover, extensions that use the machine agent canbe created to report user defined custom metrics. These custom metricsare base-lined and reported in the controller, just like the built-inmetrics.

All metrics can be accessed programmatically using a RepresentationalState Transfer (REST) API that returns either the JavaScript ObjectNotation (JSON) or the eXtensible Markup Language (XML) format. Also,the REST API can be used to query and manipulate the applicationenvironment.

Snapshots provide a detailed picture of a given application at a certainpoint in time. Snapshots usually include call graphs that allow thatenables drilling down to the line of code that may be causingperformance problems. The most common snapshots are transactionsnapshots.

FIG. 4 illustrates an example application intelligence platform (system)400 for performing one or more aspects of the techniques herein. Thesystem 400 in FIG. 4 includes client device 405 and 492, mobile device415, network 420, network server 425, application servers 430, 440, 450,and 460, asynchronous network machine 470, data stores 480 and 485,controller 490, and data collection server 495. The controller 490 caninclude visualization system 496 for providing displaying of the reportgenerated for performing the field name recommendations for fieldextraction as disclosed in the present disclosure. In someimplementations, the visualization system 496 can be implemented in aseparate machine (e.g., a server) different from the one hosting thecontroller 490.

Client device 405 may include network browser 410 and be implemented asa computing device, such as for example a laptop, desktop, workstation,or some other computing device. Network browser 410 may be a clientapplication for viewing content provided by an application server, suchas application server 430 via network server 425 over network 420.

Network browser 410 may include agent 412. Agent 412 may be installed onnetwork browser 410 and/or client 405 as a network browser add-on,downloading the application to the server, or in some other manner.Agent 412 may be executed to monitor network browser 410, the operatingsystem of client 405, and any other application, API, or anothercomponent of client 405. Agent 412 may determine network browsernavigation timing metrics, access browser cookies, monitor code, andtransmit data to data collection 495, controller 490, or another device.Agent 412 may perform other operations related to monitoring a requestor a network at client 405 as discussed herein including reportgenerating.

Mobile device 415 is connected to network 420 and may be implemented asa portable device suitable for sending and receiving content over anetwork, such as for example a mobile phone, smart phone, tabletcomputer, or other portable device. Both client device 405 and mobiledevice 415 may include hardware and/or software configured to access aweb service provided by network server 425.

Mobile device 415 may include network browser 417 and an agent 419.Mobile device may also include client applications and other code thatmay be monitored by agent 419. Agent 419 may reside in and/orcommunicate with network browser 417, as well as communicate with otherapplications, an operating system, APIs and other hardware and softwareon mobile device 415. Agent 419 may have similar functionality as thatdescribed herein for agent 412 on client 405, and may report data todata collection server 495 and/or controller 490.

Network 420 may facilitate communication of data among differentservers, devices and machines of system 400 (some connections shown withlines to network 420, some not shown). The network may be implemented asa private network, public network, intranet, the Internet, a cellularnetwork, Wi-Fi network, VoIP network, or a combination of one or more ofthese networks. The network 420 may include one or more machines such asload balance machines and other machines.

Network server 425 is connected to network 420 and may receive andprocess requests received over network 420. Network server 425 may beimplemented as one or more servers implementing a network service, andmay be implemented on the same machine as application server 430 or oneor more separate machines. When network 420 is the Internet, networkserver 425 may be implemented as a web server.

Application server 430 communicates with network server 425, applicationservers 440 and 450, and controller 490. Application server 450 may alsocommunicate with other machines and devices (not illustrated in FIG. 4).Application server 430 may host an application or portions of adistributed application. The host application 432 may be in one of manyplatforms, such as including a Java, PHP, .Net, and Node.JS, beimplemented as a Java virtual machine, or include some other host type.Application server 430 may also include one or more agents 434 (i.e.,“modules”), including a language agent, machine agent, and networkagent, and other software modules. Application server 430 may beimplemented as one server or multiple servers as illustrated in FIG. 4.

Application 432 and other software on application server 430 may beinstrumented using byte code insertion, or byte code instrumentation(BCI), to modify the object code of the application or other software.The instrumented object code may include code used to detect callsreceived by application 432, calls sent by application 432, andcommunicate with agent 434 during execution of the application. BCI mayalso be used to monitor one or more sockets of the application and/orapplication server in order to monitor the socket and capture packetscoming over the socket.

In some embodiments, server 430 may include applications and/or codeother than a virtual machine. For example, servers 430, 440, 450, and460 may each include Java code, .Net code, PHP code, Ruby code, C code,C++ or other binary code to implement applications and process requestsreceived from a remote source. References to a virtual machine withrespect to an application server are intended to be for exemplarypurposes only.

Agents 434 on application server 430 may be installed, downloaded,embedded, or otherwise provided on application server 430. For example,agents 434 may be provided in server 430 by instrumentation of objectcode, downloading the agents to the server, or in some other manner.Agent 434 may be executed to monitor application server 430, monitorcode running in a virtual machine 432 (or other program language, suchas a PHP, .Net, or C program), machine resources, network layer data,and communicate with byte instrumented code on application server 430and one or more applications on application server 430.

Each of agents 434, 444, 454, and 464 may include one or more agents,such as language agents, machine agents, and network agents. A languageagent may be a type of agent that is suitable to run on a particularhost. Examples of language agents include a Java agent, .Net agent, PHPagent, and other agents. The machine agent may collect data from aparticular machine on which it is installed. A network agent may capturenetwork information, such as data collected from a socket.

Agent 434 may detect operations such as receiving calls and sendingrequests by application server 430, resource usage, and incomingpackets. Agent 434 may receive data, process the data, for example byaggregating data into metrics, and transmit the data and/or metrics tocontroller 490. Agent 434 may perform other operations related tomonitoring applications and application server 430 as discussed herein.For example, agent 434 may identify other applications, share businesstransaction data, aggregate detected runtime data, and other operations.

An agent may operate to monitor a node, tier of nodes, or other entity.A node may be a software program or a hardware component (e.g., memory,processor, and so on). A tier of nodes may include a plurality of nodeswhich may process a similar business transaction, may be located on thesame server, may be associated with each other in some other way, or maynot be associated with each other.

A language agent may be an agent suitable to instrument or modify,collect data from, and reside on a host. The host may be a Java, PHP,.Net, Node.JS, or other type of platform. Language agents may collectflow data as well as data associated with the execution of a particularapplication. The language agent may instrument the lowest level of theapplication to gather the flow data. The flow data may indicate whichtier is communicating with which tier and on which port. In someinstances, the flow data collected from the language agent includes asource IP, a source port, a destination IP, and a destination port. Thelanguage agent may report the application data and call chain data to acontroller. The language agent may report the collected flow dataassociated with a particular application to a network agent.

A network agent may be a standalone agent that resides on the host andcollects network flow group data. The network flow group data mayinclude a source IP, destination port, destination IP, and protocolinformation for network flow received by an application on which networkagent is installed. The network agent may collect data by interceptingand performing packet capture on packets coming in from one or morenetwork interfaces (e.g., so that data generated/received by all theapplications using sockets can be intercepted). The network agent mayreceive flow data from a language agent that is associated withapplications to be monitored. For flows in the flow group data thatmatch flow data provided by the language agent, the network agent rollsup the flow data to determine metrics such as TCP throughput, TCP loss,latency, and bandwidth. The network agent may then report the metrics,flow group data, and call chain data to a controller. The network agentmay also make system calls at an application server to determine systeminformation, such as for example a host status check, a network statuscheck, socket status, and other information.

A machine agent, which may be referred to as an infrastructure agent,may reside on the host and collect information regarding the machinewhich implements the host. A machine agent may collect and generatemetrics from information such as processor usage, memory usage, andother hardware information.

Each of the language agent, network agent, and machine agent may reportdata to the controller. Controller 490 may be implemented as a remoteserver that communicates with agents located on one or more servers ormachines. The controller may receive metrics, call chain data and otherdata, correlate the received data as part of a distributed transaction,and report the correlated data in the context of a distributedapplication implemented by one or more monitored applications andoccurring over one or more monitored networks. The controller mayprovide reports, one or more user interfaces, and other information fora user.

Agent 434 may create a request identifier for a request received byserver 430 (for example, a request received by a client 405 or 415associated with a user or another source). The request identifier may besent to client 405 or mobile device 415, whichever device sent therequest. In embodiments, the request identifier may be created when datais collected and analyzed for a particular business transaction.

Each of application servers 440, 450, and 460 may include an applicationand agents. Each application may run on the corresponding applicationserver. Each of applications 442, 452, and 462 on application servers440-460 may operate similarly to application 432 and perform at least aportion of a distributed business transaction. Agents 444, 454, and 464may monitor applications 442-462, collect and process data at runtime,and communicate with controller 490. The applications 432, 442, 452, and462 may communicate with each other as part of performing a distributedtransaction. Each application may call any application or method ofanother virtual machine.

Asynchronous network machine 470 may engage in asynchronouscommunications with one or more application servers, such as applicationserver 450 and 460. For example, application server 450 may transmitseveral calls or messages to an asynchronous network machine. Ratherthan communicate back to application server 450, the asynchronousnetwork machine may process the messages and eventually provide aresponse, such as a processed message, to application server 460.Because there is no return message from the asynchronous network machineto application server 450, the communications among them areasynchronous.

Data stores 480 and 485 may each be accessed by application servers suchas application server 460. Data store 485 may also be accessed byapplication server 450. Each of data stores 480 and 485 may store data,process data, and return queries received from an application server.Each of data stores 480 and 485 may or may not include an agent.

Controller 490 may control and manage monitoring of businesstransactions distributed over application servers 430-460. In someembodiments, controller 490 may receive application data, including dataassociated with monitoring client requests at client 405 and mobiledevice 415, from data collection server 495. In some embodiments,controller 490 may receive application monitoring data and network datafrom each of agents 412, 419, 434, 444, and 454 (also referred to hereinas “application monitoring agents”). Controller 490 may associateportions of business transaction data, communicate with agents toconfigure collection of data, and provide performance data and reportingthrough an interface. The interface may be viewed as a web-basedinterface viewable by client device 492, which may be a mobile device,client device, or any other platform for viewing an interface providedby controller 490. In some embodiments, a client device 492 may directlycommunicate with controller 490 to view an interface for monitoringdata.

Client device 492 may include any computing device, including a mobiledevice or a client computer such as a desktop, work station or othercomputing device. Client computer 492 may communicate with controller490 to create and view a custom interface. In some embodiments,controller 490 provides an interface for creating and viewing the custominterface as a content page, e.g., a web page, which may be provided toand rendered through a network browser application on client device 492.

Applications 432, 442, 452, and 462 may be any of several types ofapplications. Examples of applications that may implement applications432-462 include a Java, PHP, .Net, Node.JS, and other applications.

FIG. 5 is a block diagram of a computer system 500 for implementing thepresent technology, which is a specific implementation of device 200 ofFIG. 2 above. System 500 of FIG. 5 may be implemented in the contexts ofthe likes of clients 405, 492, network server 425, servers 430, 440,450, 460, asynchronous network machine 470, and controller 490 of FIG.4. (Note that the specifically configured system 500 of FIG. 5 and thecustomized device 200 of FIG. 2 are not meant to be mutually exclusive,and the techniques herein may be performed by any suitably configuredcomputing device.)

The computing system 500 of FIG. 5 includes one or more processors 510and memory 520. Main memory 520 stores, in part, instructions and datafor execution by processor 510. Main memory 520 can store the executablecode when in operation. The system 500 of FIG. 5 further includes a massstorage device 530, portable storage medium drive(s) 540, output devices550, user input devices 560, a graphics display 570, and peripheraldevices 580.

The components shown in FIG. 5 are depicted as being connected via asingle bus 590. However, the components may be connected through one ormore data transport means. For example, processor unit 510 and mainmemory 520 may be connected via a local microprocessor bus, and the massstorage device 530, peripheral device(s) 580, portable or remote storagedevice 540, and display system 570 may be connected via one or moreinput/output (I/O) buses.

Mass storage device 530, which may be implemented with a magnetic diskdrive or an optical disk drive, is a non-volatile storage device forstoring data and instructions for use by processor unit 510. Massstorage device 530 can store the system software for implementingembodiments of the present disclosure for purposes of loading thatsoftware into main memory 520.

Portable storage device 540 operates in conjunction with a portablenon-volatile storage medium, such as a compact disk, digital video disk,magnetic disk, flash storage, etc. to input and output data and code toand from the computer system 500 of FIG. 5. The system software forimplementing embodiments of the present disclosure may be stored on sucha portable medium and input to the computer system 500 via the portablestorage device 540.

Input devices 560 provide a portion of a user interface. Input devices560 may include an alpha-numeric keypad, such as a keyboard, forinputting alpha-numeric and other information, or a pointing device,such as a mouse, a trackball, stylus, or cursor direction keys.Additionally, the system 500 as shown in FIG. 5 includes output devices550. Examples of suitable output devices include speakers, printers,network interfaces, and monitors.

Display system 570 may include a liquid crystal display (LCD) or othersuitable display device. Display system 570 receives textual andgraphical information, and processes the information for output to thedisplay device.

Peripherals 580 may include any type of computer support device to addadditional functionality to the computer system. For example, peripheraldevice(s) 580 may include a modem or a router.

The components contained in the computer system 500 of FIG. 5 caninclude a personal computer, hand held computing device, telephone,mobile computing device, workstation, server, minicomputer, mainframecomputer, or any other computing device. The computer can also includedifferent bus configurations, networked platforms, multi-processorplatforms, etc. Various operating systems can be used including Unix,Linux, Windows, Apple OS, and other suitable operating systems,including mobile versions.

When implementing a mobile device such as smart phone or tabletcomputer, the computer system 500 of FIG. 5 may include one or moreantennas, radios, and other circuitry for communicating over wirelesssignals, such as for example communication using Wi-Fi, cellular, orother wireless signals.

Automatic Detection and Prevention of Injection Attacks

As noted above, applications are built on different frameworks andlibraries which may inherently have security loopholes, making themvulnerable. Despite using framework security features and other securityapplications, customer applications are vulnerable to security riskslike injection flaws, and sensitive data exposure. Current technologiesprovide for code analysis that needs to be done prior to deployment,however static code analysis is insufficient as security vulnerabilitiescan exist even after this initial code analysis.

According to the Open Web Application Security Project (OWASP), aprimary source of web application security guidelines, one of the topten application threats continues to be injection attacks. Injectionflaws, such as Structured Query Language (SQL), Not only SQL (NoSQL),and Lightweight Directory Access Protocol (LDAP) injection occur whenuntrusted data is sent to an interpreter as part of a command or query.The attacker's hostile data can trick the interpreter into executingunintended commands or accessing data without proper authorization.Hackers thus can use stealth techniques to go unnoticed for as long aspossible, and injection attacks are becoming increasingly sophisticatedand difficult to combat. Injection attacks have been responsible forwidespread information breaches of personal and financial informationover recent years.

The techniques herein, therefore, provide automatic detection andprevention of injection attacks on an application, as a measure ofruntime security protection. In particular, the techniques herein enableapplications to protect themselves, i.e., establishing self-protectingsoftware.

Specifically, in one embodiment, the techniques herein receive aninjected command to be executed by an application from an applicationmonitoring agent operating in the network, where the injected command isintercepted by the application monitoring agent prior to execution ofthe injected command by the application; determine whether the injectedcommand is malicious using a security algorithm; enable the applicationto execute the injected command when it is determined that the injectedcommand is not malicious; and prevent the application from executing theinjected command when it is determined that the injected command ismalicious.

Notably, the techniques herein may employ any number of machine learningtechniques, such as to detect injection attacks as described herein. Ingeneral, machine learning is concerned with the design and thedevelopment of techniques that receive empirical data as input (e.g.,collected metric/event data from agents, sensors, etc.) and recognizecomplex patterns in the input data. For example, some machine learningtechniques use an underlying model M, whose parameters are optimized forminimizing the cost function associated to M, given the input data. Forinstance, in the context of classification, the model M may be astraight line that separates the data into two classes (e.g., labels)such that M=a*x+b*y+c and the cost function is a function of the numberof misclassified points. The learning process then operates by adjustingthe parameters a,b,c such that the number of misclassified points isminimal. After this optimization/learning phase, the techniques hereincan use the model M to classify new data points. Often, M is astatistical model, and the cost function is inversely proportional tothe likelihood of M, given the input data.

One class of machine learning techniques that is of particular useherein is clustering. Generally speaking, clustering is a family oftechniques that seek to group data according to some typicallypredefined or otherwise determined notion of similarity.

Also, the performance of a machine learning model can be evaluated in anumber of ways based on the number of true positives, false positives,true negatives, and/or false negatives of the model.

In various embodiments, such techniques may employ one or moresupervised, unsupervised, or semi-supervised machine learning models.Generally, supervised learning entails the use of a training set ofdata, as noted above, that is used to train the model to apply labels tothe input data. On the other end of the spectrum are unsupervisedtechniques that do not require a training set of labels. Notably, whilea supervised learning model may look for previously seen patterns thathave been labeled as such, an unsupervised model may attempt to analyzethe data without applying a label to it. Semi-supervised learning modelstake a middle ground approach that uses a greatly reduced set of labeledtraining data.

Example machine learning techniques that the techniques herein canemploy may include, but are not limited to, nearest neighbor (NN)techniques (e.g., k-NN models, replicator NN models, etc.), statisticaltechniques (e.g., Bayesian networks, etc.), clustering techniques (e.g.,k-means, mean-shift, etc.), neural networks (e.g., reservoir networks,artificial neural networks, etc.), support vector machines (SVMs),logistic or other regression, Markov models or chains, principalcomponent analysis (PCA) (e.g., for linear models), multi-layerperceptron (MLP) artificial neural networks (ANNs) (e.g., for non-linearmodels), replicating reservoir networks (e.g., for non-linear models,typically for time series), random forest classification, or the like.

Operationally, application performance management/monitoring (APM)offers information technology (IT) and Security teams unprecedentedvisibility into their applications' performance, helping them discoverand troubleshoot issues before they become a hindrance. Security can beviewed as another facet of application monitoring. Applications rely onvarious frameworks and libraries which can have security loopholes.Security Teams constantly monitor hardware and software for possiblesecurity breaches and ensure that the latest security patches areimplemented to avoid known exploits by hackers.

The techniques herein thus provide runtime instrumentation to evaluateinjected commands directly before execution and help to catch thesevulnerabilities before being exploited. Security risks like SQLinjection and command injection attacks can be averted as these arealready being instrumented by the APM (e.g., the applicationintelligence platform described above). The placement of APM agents assensors that actively work inside applications can be leveraged toprovide an inbuilt security mechanism to applications.

The techniques herein, with reference generally to FIG. 6 illustratingan example simplified architecture 600 for automatic detection andprevention of injection attacks in accordance with one or moreembodiments described herein, specifically achieve this by utilizingJavaAgent functionality in an APM agent to intercept an injectedcommand, e.g., a SQL query, an operating system (OS) command, etc.,right before it is being executed, consistent with runtimeinstrumentation, which provides a complete visibility of the command forwhich execution is being attempted. A security algorithm (e.g., policy,threshold scoring, code matching, machine learning, etc.) may be run onthe intercepted command (query check) to identify malicious intent. Ifidentified as malicious, execution of the injected command can bestopped and/or the injected command can be flagged. Conversely, if theinjected command is not determined to be malicious, the application mayproceed to execute the injected command in its normal course ofoperation.

As shown in FIG. 6, an application 610 may be operating (e.g., on acorresponding application server). The application 610 may be, forexample, a customer-owned application, such as application 432, 442,452, 462, etc. The application 610 is not limited to any particular typeof application, but may be any of several types of applications. Theapplication 610 may be built and implemented on various platforms suchas Java, PHP, .Net, Node.JS, and so forth. Furthermore, the application610 may be in communication with a database or server 620, such asapplication servers 430-460, datastores 480 and 485, or the like.

As mentioned above, performance of the application 610 may be activelymonitored as part of an application performance management/monitoring(APM) system. In this regard, an application monitoring agent 630 (“APMagent”) may be implemented as a sensor that actively works insideapplication 610 to collect information associated with the applicationto provide, not only performance monitoring in various forms, but alsosecurity monitoring. Specifically, the agent 630 (e.g., agent 434, 444,454, 464, etc.) may be used to carry out runtime instrumentation of theapplication 610 to monitor and evaluate commands inputted to theapplication 610 prior to execution of the commands.

Particularly, an injected command 640 may be inputted to the application610 for execution by the application 610. The injected command 640 maybe provided, i.e., “injected,” to the application 610 as input via auser interface of the application 610 (e.g., a query/input bar, acommand line, etc.), for example, as may be carried out in an injectionattack. The injected command 640 may be any type of command or datacapable of being provided as input to the application 610 including, butnot limited to, a SQL query, an operating system (OS) command, an XPathquery, an electronic communication (e.g., email), a carriage return andline feed (CRLF) command, and the like.

In the normal course of operation, the application 610 would execute theinjected command 640. However, certain commands may be processed by aninterpreter (e.g., Java, PHP, .Net, Node.JS, etc.) running on theapplication 610 as part of a command or query which alters the normalcourse of execution of the application, potentially in a harmful ormalicious manner. Such an attack is known as an injection attack, asdescribed above, whereby an untrusted command is injected to anapplication or program, potentially resulting in data theft, data loss,loss of data integrity, denial of service, or even full systemcompromise. To prevent such attacks, the agent 630 may intercept theinjected command 640, which has been inputted to the application 610(e.g., via a user interface of the application 610) at runtime, that is,directly prior to the application 610 executing the potentiallymalicious command 640.

The injected command 640 may then be checked or evaluated to determinewhether or not the command is malicious (or likely to be malicious). Inone embodiment, the agent 630 may provide the injected command 640 to acontroller (e.g., controller 490), a server (e.g., network server 425,application servers 430-460, etc.), or other remote processing devicefor analysis. Assuming for demonstration purposes the controller 490receives the injected command 640 from the agent 630 (though the presentembodiments are not limited thereto), the controller 490 may perform aquery check 650 to determine the potential maliciousness of the injectedcommand 640.

In one embodiment, the controller 490 may use a security algorithm todetermine whether or not the injected command 640 is malicious (orlikely to be malicious). For example, the security algorithm may be amachine learning-based model trained with examples of malicious injectedcommands as input. The machine learning-based model may apply clusteringor pattern matching techniques, for example, as described above, todetermine a similarity between the injected command 640 and othermalicious injected commands used as training data. In some embodiments,a “malice score” may be calculated for the injected command 640 as anumerical indicator of the similarity between the injected command 640and the other malicious injected commands, that is, a likelihood ofmalicious intent. For example, the security algorithm may be used toidentify aspects of the injected command 640 associated with othermalicious injected commands, such as particular characters or syntaxwhich trigger a response in the application query interpreter,particular strings or commands which trigger a response in theapplication query interpreter, requests for user-identifyinginformation, requests to alter database records, and the like. As thenumber of such malicious aspects increases, so too may the malice score.The malice score may then be compared by the controller 490 to apredefined safety threshold above which, for example, the injectedcommand 640 is deemed malicious, and below which, for example, theinjected command is deemed safe for execution by the application 610. Insome embodiments, the safety threshold may be upwardly or downwardlyadjusted by the customer to allow for custom or tailored injectionattack detection.

If it is determined that the injected command 640 is not malicious,i.e., the query check 650 passes, the controller 490 can enable orinstruct the application 610 proceed with execution of the command 640.In other words, the injected command 640 may be deemed safe in suchcase, and the application 610 can execute the command 640 in line withits normal course of operation.

Conversely, it is determined that the injected command 640 is malicious(or likely to be malicious), i.e., the query check 650 fails, thecontroller 490 may take various remedial actions including, for example,blocking the injected command 640 so as to prevent the application 640from executing the injected command 640, thereby potentially thwartingan injection attack from an external attacker. Additional remedialactions may be taken by the controller 490 including, but not limitedto, notifying a user or customer of the potential injection attack viaan application monitoring visualization system (e.g., visualizationsystem 350, 496, etc.), as described in greater detail below withrespect to FIGS. 7A, 7B, 8A, and 8B.

FIGS. 7A and 7B illustrate an example of SQL injection prevention inaccordance with one or more embodiments described herein. As shown inFIG. 7A, when a malicious injected command is detected, a user can bealerted to the potential issue (e.g., a SQL Filter alert) via anapplication monitoring visualization system which includes a graphicaluser interface (GUI) 700. Importantly, the application monitoringvisualization system can notify the user that a “user experience error”has occurred, resulting from an identified malicious command, before theinjected command 640 has been executed by the application 610. Inaddition, the application monitoring visualization system may displayvia the GUI 700 an option to “drill down” into the error caused by thepotential injection attack in order to receive additional informationregarding the error.

In response to receiving said request for additional information, theapplication monitoring visualization system may display via the GUI 700information regarding the detected injected command 640 and potentialinjection attack. For example, as shown in 710 of FIG. 7B, the detectedinjected command 640 itself can be displayed (e.g., “Query: select *from user_data where last_name=‘erwin’ or ‘1’=‘1’”). Furthermore,various characterizations of the injected command 640 can be providedincluding, for example, an error code (e.g., “MaliciousCodeException”),a description of the injected command 640 and/or an explanation of whythe injected command 640 was flagged (e.g., “Tautology based injection:Usage of anyString=anyString”), or the like. In some embodiments, anoption can be provided via the GUI 700 to enable the user to instructthe controller 490 to discard the injected command 640, thus preventingthe potential injection attack. Additionally, an option can be providedvia the GUI 700 to enable the user to compel the application 610 toexecute the injected command 640 if the user believes the command 640 issafe, thereby effectively overriding the preventative actions taken bythe controller 490 and agent 630.

Similarly, FIGS. 8A and 8B illustrate an example of OS command injectionprevention in accordance with one or more embodiments described herein.In particular, here, an injected OS command may be flagged aspotentially malicious. As shown in FIG. 8A, a user can be alerted to thepotential issue via the GUI 700 of the application monitoringvisualization system before the injected command 640 has been executedby the application 610. The application monitoring visualization systemmay again display via the GUI 700 an option to “drill down” into theerror caused by the potential injection attack in order to receiveadditional information regarding the error.

In response to receiving said request for additional information, theapplication monitoring visualization system may display via the GUI 700information regarding the detected injected command 640 and potentialinjection attack, as described above. For example, as shown in 810 ofFIG. 8B, the detected injected command 640 itself can be displayed(e.g., “/bin/sh -c cat“/Users/shrenik.jain/Desktop/.extract/webapps/WebGoat/plugin_extracted/plugin/CommandInjection/resources/AccessControlMatrix.html “& netstat -an &ipconfig””). Furthermore, various characterizations of the injectedcommand 640 can be provided including, for example, an error code (e.g.,“MaliciousCodeException”), a description of the injected command 640and/or an explanation of why the injected command 640 was flagged (e.g.,“Command Injection Found”), or the like.

Both examples above may further indicate many instrumented metrics fromthe APM agent, such as timestamps, execution time, node/location,transaction ID, and so on. This information may be of particular use indiagnosing the errors and/or for root cause analysis.

In closing, FIG. 9 illustrates an example simplified procedure forenhanced web application security communication in accordance with oneor more embodiments described herein. For example, a non-generic,specifically configured device (e.g., device 200) may perform procedure900 by executing stored instructions (e.g., process 248). The procedure900 may start at step 905, and continues to step 910, where, asdescribed in greater detail above, the techniques herein receive aninjected command (e.g., injected command 640) to be executed by anapplication (e.g., application 610) from an application monitoring agent(e.g., agent 630) operating in a network. As described above, theinjected command may be intercepted by the application monitoring agent(e.g., using inherent Java Agent functionality) prior to execution ofthe injected command by the application as a part of runtimeinstrumentation of the application.

In step 915, the techniques herein determine whether the injectedcommand is malicious using a security algorithm. As described above, thesecurity algorithm may be a machine learning-based model trained withexamples of malicious injected commands as input, for example. In someembodiments, a “malice score” may be calculated for the injected commandas a numerical indicator of the similarity between the injected commandand the other malicious injected commands, thereby characterizing alikelihood of malicious intent. The malice score may then be compared toa predefined safety threshold above which, for example, the injectedcommand is deemed malicious, and below which, for example, the injectedcommand is deemed safe for execution by the application.

In step 920, the techniques herein identify whether malicious intent ofthe injected command is present based on the security algorithm. Ifidentified as malicious in step 920, the techniques herein may thenprevent the execution of the injected command in step 925. Furthermore,in such case, additional remedial actions may be taken including, butnot limited to, notifying the user of the potential injection attack viaan application monitoring visualization system (e.g., visualizationsystem 350, 496, etc.), as described in greater detail above.

Alternatively, if not identified as malicious in step 920, thetechniques herein may then enable the application to execute theinjected command in its normal course of operation in step 930.

The illustrative simplified procedure may then end in step 935.

It should be noted that while certain steps within procedure 900 may beoptional as described above, the steps shown in FIG. 9 are merelyexamples for illustration, and certain other steps may be included orexcluded as desired. Further, while a particular order of the steps isshown, this ordering is merely illustrative, and any suitablearrangement of the steps may be utilized without departing from thescope of the embodiments herein.

The techniques described herein, therefore, provide for automaticdetection and prevention of injection attacks. In particular, thetechniques herein go beyond the conventional technologies that performstatic checking of stored files/programs to adjust settings andprivileges prior to releasing the application to the public, whereas thetechniques herein may be used during runtime implementation, mitigatinginjection attacks on applications that may not have had vulnerabilitiesremoved in advance, or, even further, on applications that havedeveloped or that have been exposed to new vulnerabilities. Unlikeconventional systems, too, the techniques herein integrate security withapplication performance monitoring (e.g., the application intelligenceplatform above), establishing a holistic application monitoring modelwhich not only helps to monitor performance, but also to combatpotential security risks to an application that may affect itsperformance. Said differently, the techniques herein expand performancemonitoring and business monitoring solutions to include runtime securityprotection as a complete application monitoring product.

In still further embodiments of the techniques herein, a business impactof the injection attacks can also be quantified. That is, because ofissues related to specific applications/processes (e.g., lost traffic,slower servers, overloaded network links, etc.), various correspondingbusiness transactions may have been correspondingly affected for thoseapplications/processes (e.g., online purchases were delayed, page visitswere halted before fully loading, user satisfaction or dwell timedecreased, etc.), while other processes (e.g., on other network segmentsor at other times) remain unaffected. The techniques herein, therefore,can correlate the injection attacks with various business transactionsin order to better understand the effect on the business transactions,accordingly.

Illustratively, the techniques described herein may be performed byhardware, software, and/or firmware, such as in accordance with theillustrative injection attack mitigation process 248, which may includecomputer executable instructions executed by the processor 220 toperform functions relating to the techniques described herein, e.g., inconjunction with corresponding processes of other devices in thecomputer network as described herein (e.g., on network agents,controllers, computing devices, servers, etc.).

According to the embodiments herein, a method herein may specificallycomprise: receiving, by a controller in a network, an injected commandto be executed by an application from an application monitoring agentoperating in the network, the injected command intercepted by theapplication monitoring agent prior to execution of the injected commandby the application; determining, by the controller, whether the injectedcommand is malicious using a security algorithm; enabling, by thecontroller, the application to execute the injected command when it isdetermined that the injected command is not malicious; and preventing,by the controller, the application from executing the injected commandwhen it is determined that the injected command is malicious.

In one embodiment, prior to the receiving of the injected command by thecontroller, the injected command may be inputted for execution by theapplication via an interface of the application. In one embodiment, theapplication monitoring agent may be configured to intercept commandsinputted via the interface of the application at runtime. In oneembodiment, the application monitoring agent may be installed at anapplication server and is further configured to monitor operation of theapplication. In one embodiment, the method may further comprisenotifying, by the controller, a user of a potential injection attack viaan application monitoring visualization system when it is determinedthat the injected command is malicious. In one embodiment, the methodmay further comprise receiving, by the controller, a request foradditional information regarding the potential injection attack via theapplication monitoring visualization system. In one embodiment, themethod may further comprise displaying, by the controller, at least oneof the injected command and a characterization of the potentialinjection attack via the application monitoring visualization system inresponse to the request for additional information regarding thepotential injection attack. In one embodiment, the method may furthercomprise providing, by the controller, an option for a user to compelthe application to execute the injected command via an applicationmonitoring visualization system when it is determined that the injectedcommand is malicious. In one embodiment, the injected command mayinclude a SQL query or an operating system (OS) command. In oneembodiment, the security algorithm may be a machine learning-based modeltrained with examples of malicious injected commands as input. In oneembodiment, the determining of whether the injected command is maliciousmay further comprise calculating, by the controller, a malice scoreindicating a likelihood of malicious intent using the securityalgorithm; and determining, by the controller, that the injected commandis malicious when the malice score exceeds a predefined threshold. Inone embodiment, the determining of whether the injected command ismalicious may further comprise identifying, by the controller, one ormore aspects of the injected command associated with other maliciousinjected commands using the security algorithm.

According to the embodiments herein, a tangible, non-transitory,computer-readable medium herein may have computer-executableinstructions stored thereon that, when executed by a processor on acomputer, may cause the computer to perform a method specificallycomprising: receiving an injected command to be executed by anapplication from an application monitoring agent operating in a network,the injected command intercepted by the application monitoring agentprior to execution of the injected command by the application;determining whether the injected command is malicious using a securityalgorithm; enabling the application to execute the injected command whenit is determined that the injected command is not malicious; andpreventing the application from executing the injected command when itis determined that the injected command is malicious.

Further, according to the embodiments herein an apparatus herein mayspecifically comprise: one or more network interfaces to communicatewith a network; a processor coupled to the network interfaces andconfigured to execute one or more processes; and a memory configured tostore a process executable by the processor, the process, when executed,configured to: receive an injected command to be executed by anapplication from an application monitoring agent operating in thenetwork, the injected command intercepted by the application monitoringagent prior to execution of the injected command by the application;determine whether the injected command is malicious using a securityalgorithm; enable the application to execute the injected command whenit is determined that the injected command is not malicious; and preventthe application from executing the injected command when it isdetermined that the injected command is malicious.

While there have been shown and described illustrative embodimentsabove, it is to be understood that various other adaptations andmodifications may be made within the scope of the embodiments herein.For example, while certain embodiments are described herein with respectto certain types of networks in particular, the techniques are notlimited as such and may be used with any computer network, generally, inother embodiments. Moreover, while specific technologies, protocols, andassociated devices have been shown, such as Java, TCP, IP, and so on,other suitable technologies, protocols, and associated devices may beused in accordance with the techniques described above. In addition,while certain devices are shown, and with certain functionality beingperformed on certain devices, other suitable devices and processlocations may be used, accordingly. That is, the embodiments have beenshown and described herein with relation to specific networkconfigurations (orientations, topologies, protocols, terminology,processing locations, etc.). However, the embodiments in their broadersense are not as limited, and may, in fact, be used with other types ofnetworks, protocols, and configurations.

Moreover, while the present disclosure contains many other specifics,these should not be construed as limitations on the scope of anyembodiment or of what may be claimed, but rather as descriptions offeatures that may be specific to particular embodiments of particularembodiments. Certain features that are described in this document in thecontext of separate embodiments can also be implemented in combinationin a single embodiment. Conversely, various features that are describedin the context of a single embodiment can also be implemented inmultiple embodiments separately or in any suitable sub-combination.Further, although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asub-combination or variation of a sub-combination.

For instance, while certain aspects of the present disclosure aredescribed in terms of being performed “by a server” or “by acontroller”, those skilled in the art will appreciate that agents of theapplication intelligence platform (e.g., application agents, networkagents, language agents, etc.) may be considered to be extensions of theserver (or controller) operation, and as such, any process stepperformed “by a server” need not be limited to local processing on aspecific server device, unless otherwise specifically noted as such.Furthermore, while certain aspects are described as being performed “byan agent” or by particular types of agents (e.g., application agents,network agents, etc.), the techniques may be generally applied to anysuitable software/hardware configuration (libraries, modules, etc.) aspart of an apparatus or otherwise.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. Moreover, the separation of various system components in theembodiments described in the present disclosure should not be understoodas requiring such separation in all embodiments.

The foregoing description has been directed to specific embodiments. Itwill be apparent, however, that other variations and modifications maybe made to the described embodiments, with the attainment of some or allof their advantages. For instance, it is expressly contemplated that thecomponents and/or elements described herein can be implemented assoftware being stored on a tangible (non-transitory) computer-readablemedium (e.g., disks/CDs/RAM/EEPROM/etc.) having program instructionsexecuting on a computer, hardware, firmware, or a combination thereof.Accordingly, this description is to be taken only by way of example andnot to otherwise limit the scope of the embodiments herein. Therefore,it is the object of the appended claims to cover all such variations andmodifications as come within the true intent and scope of theembodiments herein.

What is claimed is:
 1. A method, comprising: receiving, by a controllerin a network, an injected command to be executed by an application froman application monitoring agent operating in the network, the injectedcommand intercepted by the application monitoring agent prior toexecution of the injected command by the application; determining, bythe controller, whether the injected command is malicious using asecurity algorithm; enabling, by the controller, the application toexecute the injected command when it is determined that the injectedcommand is not malicious; and preventing, by the controller, theapplication from executing the injected command when it is determinedthat the injected command is malicious.
 2. The method as in claim 1,wherein, prior to the receiving of the injected command by thecontroller, the injected command is inputted for execution by theapplication via an interface of the application.
 3. The method as inclaim 2, wherein the application monitoring agent is configured tointercept commands inputted via the interface of the application atruntime.
 4. The method as in claim 1, wherein the application monitoringagent is installed at an application server and is further configured tomonitor operation of the application.
 5. The method as in claim 1,further comprising: notifying, by the controller, a user of a potentialinjection attack via an application monitoring visualization system whenit is determined that the injected command is malicious.
 6. The methodas in claim 5, further comprising: receiving, by the controller, arequest for additional information regarding the potential injectionattack via the application monitoring visualization system.
 7. Themethod as in claim 6, further comprising: displaying, by the controller,at least one of the injected command and a characterization of thepotential injection attack via the application monitoring visualizationsystem in response to the request for additional information regardingthe potential injection attack.
 8. The method as in claim 1, furthercomprising: providing, by the controller, an option for a user to compelthe application to execute the injected command via an applicationmonitoring visualization system when it is determined that the injectedcommand is malicious.
 9. The method as in claim 1, wherein the injectedcommand includes a Structured Query Language (SQL) query or an operatingsystem (OS) command.
 10. The method as in claim 1, wherein the securityalgorithm is a machine learning-based model trained with examples ofmalicious injected commands as input.
 11. The method as in claim 1,wherein the determining of whether the injected command is maliciouscomprises: calculating, by the controller, a malice score indicating alikelihood of malicious intent using the security algorithm; anddetermining, by the controller, that the injected command is maliciouswhen the malice score exceeds a predefined threshold.
 12. The method asin claim 1, wherein the determining of whether the injected command ismalicious comprises: identifying, by the controller, one or more aspectsof the injected command associated with other malicious injectedcommands using the security algorithm.
 13. A tangible, non-transitory,computer-readable medium having computer-executable instructions storedthereon that, when executed by a processor on a computer, cause thecomputer to perform a method comprising: receiving an injected commandto be executed by an application from an application monitoring agentoperating in a network, the injected command intercepted by theapplication monitoring agent prior to execution of the injected commandby the application; determining whether the injected command ismalicious using a security algorithm; enabling the application toexecute the injected command when it is determined that the injectedcommand is not malicious; and preventing the application from executingthe injected command when it is determined that the injected command ismalicious.
 14. The computer-readable medium as in claim 13, wherein,prior to the receiving of the injected command, the injected command isinputted for execution by the application via an interface of theapplication.
 15. The computer-readable medium as in claim 14, whereinthe application monitoring agent is configured to intercept commandsinputted via the interface of the application at runtime.
 16. Thecomputer-readable medium as in claim 15, wherein the applicationmonitoring agent is installed at an application server and is furtherconfigured to monitor operation of the application.
 17. Thecomputer-readable medium as in claim 13, the method further comprising:notifying, by the controller, a user of a potential injection attack viaa user interface when it is determined that the injected command ismalicious.
 18. The computer-readable medium as in claim 17, the methodfurther comprising: receiving, by the controller, a request foradditional information regarding the potential injection attack via theuser interface.
 19. The computer-readable medium as in claim 18, themethod further comprising: displaying, by the controller, at least oneof the injected command and a characterization of the potentialinjection attack via the user interface in response to the request foradditional information regarding the potential injection attack.
 20. Anapparatus, comprising: one or more network interfaces to communicatewith a network; a processor coupled to the network interfaces andconfigured to execute one or more processes; and a memory configured tostore a process executable by the processor, the process, when executed,configured to: receive an injected command to be executed by anapplication from an application monitoring agent operating in thenetwork, the injected command intercepted by the application monitoringagent prior to execution of the injected command by the application;determine whether the injected command is malicious using a securityalgorithm; enable the application to execute the injected command whenit is determined that the injected command is not malicious; and preventthe application from executing the injected command when it isdetermined that the injected command is malicious.